Abstract
Abstract This article describes a novel method for improving image resolution achieved using time-resolved photon emission techniques. Instead of directly generating images from photon counting, all detected photons are displayed as a point cloud in 3D space and a new higher-resolution image is generated based on probability density functions associated with photon distributions. Unsupervised learning algorithms identify photon distribution patterns as well as fainter emission sources.
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